Immune gene expression analysis indicates the potential of a self-amplifying Covid-19 mRNA vaccine

Remarkable potency has been demonstrated for mRNA vaccines in reducing the global burden of the ongoing COVID-19 pandemic. An alternative form of the mRNA vaccine is the self-amplifying mRNA (sa-mRNA) vaccine, which encodes an alphavirus replicase that self-amplifies the full-length mRNA and SARS-CoV-2 spike (S) transgene. However, early-phase clinical trials of sa-mRNA COVID-19 vaccine candidates have questioned the potential of this platform to develop potent vaccines. We examined the immune gene response to a candidate sa-mRNA vaccine against COVID-19, ARCT-021, and compared our findings to the host response to other forms of vaccines. In blood samples from healthy volunteers that participated in a phase I/II clinical trial, greater induction of transcripts involved in Toll-like receptor (TLR) signalling, antigen presentation and complement activation at 1 day post-vaccination was associated with higher anti-S antibody titers. Conversely, transcripts involved in T-cell maturation at day 7 post-vaccination informed the magnitude of eventual S-specific T-cell responses. The transcriptomic signature for ARCT-021 vaccination strongly correlated with live viral vector vaccines, adjuvanted vaccines and BNT162b2 1 day post-vaccination. Moreover, the ARCT-021 signature correlated with day 7 YF17D live-attenuated vaccine transcriptomic responses. Altogether, our findings show that sa-mRNA vaccination induces innate immune responses that are associated with the development of adaptive immunity from other forms of vaccines, supporting further development of this vaccine platform for clinical application.

Supplementary figure 2. Gene regulatory networks that are induced by ARCT-021 one day following vaccination. Ingenuity pathway analysis of a subset of genes that are identified as being significantly upregulated on day 2 (False Discovery Rate [FDR]-adjusted p-value < 0.05, Benjamini-Hochberg step-up procedure).
Supplementary figure 3. Transcripts related to pattern recognition receptor signalling and MHC-I antigen presentation are upregulated one day following vaccination. Ingenuity pathway analysis showing transcripts involved in a. pattern recognition receptor signaling and b. antigen presentation that are significantly changed on day 2 (False Discovery Rate [FDR]-adjusted p-value < 0.05, Benjamini-Hochberg step-up procedure). Pink ovals indicate transcripts that are upregulated whereas green ovals indicate transcripts that are downregulated.
Supplementary figure 4. Transcripts and enriched gene sets that best distinguish C1 from C2 subjects. a. Top 10 blood transcription modules (BTMs) that are most significantly enriched in C1 compared to C2 based on differentially expressed genes (DEGs). DEGs were defined as genes with fold-change > 1.3 and False Discovery Rate [FDR]-adjusted p-value < 0.05, Benjamini-Hochberg step-up procedure. b. GO biological processes enriched among the BSIG genes. c. Day 29 IgG antibody titers and d. Day 15 S-specific T cell responses in vaccinated individuals, ranked from smallest to largest values and coloured by C1 (purple) or C2 (yellow) group.
Supplementary figure 5. Random forest regression identifies transcripts that are most predictive of antibody responses to ARCT-021. a. Schematic of random forest regression. Machine learning is based on 106 subjects enrolled into the trial using random forest regression, with 75% of the subjects grouped into the training data and 25% of subjects grouped into test data. Final model was predicted based on averaging of 1,000 decision trees. b. Feature importance of the individual transcripts that were predictive of IgG titers at day 29. The top 6 genes were then selected for hyperparameter tuning, to further refine the random forest regression model. c. Scatterplot of the predicted and observed antibody titers, where predicted values were calculated based on the random forest regression model refined in b. Accuracy, mean absolute error, root mean-squared error, Pearson coefficient and p-values of the relationship between predicted and observed values are also displayed.
Supplementary figure 6. Expression of transcripts that best distinguish responders from non-responders are not associated with severity of adverse events (AEs). a. Volcano plot displaying genes that were most differentially expressed at day 2 after vaccination in responders relative to non-responders. The most differentially regulated genes are annotated on the volcano plot. b. Expression of MSR1 and c. FCERG1 on day 2 is significantly higher in responders than nonresponders. Box plots in b-c represent 25%-75% intervals, with lines indicating medians. The whiskers represent 10%-90% intervals. Unpaired, two-sided, Student's t-tests were used for comparisons for b-c. d. Volcano plot displaying genes that were most differentially expressed at day 2 after vaccination in responders relative to nonresponders in older adults. The most differentially regulated genes are annotated on the volcano plot. e. Expression of MSR1 and f. FCERG1 on day 2 is not significantly different in subjects with varying levels of adverse event severity. Subjects with no systemic AEs were scored as 0, mild AEs as 1, moderate AEs as 2 and severe AEs as 3. g. BSIG score is not significantly different in subjects with varying levels of adverse event severity. Box plots in e-g represent 25%-75% intervals, with lines indicating medians. The whiskers represent 10%-90% intervals. Unpaired, two-sided, Student's t-tests were used for comparisons for e-g. Spike-specific T cell responses measured at day 15 in subjects from T1 and T2 clusters. Box plots in b represent 25%-75% intervals, with lines indicating medians. The whiskers represent 10%-90% intervals. c. Scatterplot of the predicted and observed antibody titers, where predicted values were calculated based on the random forest regression model using log2-transformed fold change values of CD27, PSMB5 and LEF1 on day 8. Accuracy, mean absolute error, root mean-squared error, Pearson coefficient and p-values of the relationship between predicted and observed values are presented. d. Correlation matrix showing pairwise correlations of the mean gene log2-transformed fold changes between the different vaccines at day 1 post vaccination. Size and intensity of dots are proportional to the magnitude of correlation coefficient.